System and method for influencing recommender system & advertising based on programmed policies

• US 20040260574A1
• Filed: 06/07/2004
• Published: 12/23/2004
• Est. Priority Date: 06/06/2003
• Status: Active Grant

• Current Assignee: Xylon LLC (Intellectual Ventures LLC)
• Original Assignee: Hayley Logistics LLC (Intellectual Ventures LLC)
• Inventors: Gross, John N.
• Granted Patent: US 7,689,432 B2
• Time in Patent Office: Days
• US Class Current: 705/1.1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system and method for influencing a recommender system and advertising uses a controlled, programmed policy. The recommender system uses the policy to adjust recommendations made to users for particular items, so that a policy holder receives some measure of preference in recommendations. The preference may be implemented in the form of a filter, or a presentation of items. The policy can be applied selectively, and be based on pay for placement type consideration, demographics, time, and other related parameters. Advertising for the users can be similarly adjusted in coordination with the policy.

Claims

1. A method of operating a recommender system, which recommender is used for recommending items of interest to users interacting with an online service provider, the method comprising the steps of:

(a) setting up one or more policies to be used for influencing recommendations made by the recommender system to a user;

(b) responding to a request for a recommendation;

(c) causing said recommender system to use at least one of said one or more policies when presenting one or mote policy influenced recommendations to the user in response to said request.

2. The method of claim 1 further including a step prior to (c):

evaluating said one or more policies under a cost—

benefit analysis to determine an appropriate policy to be used for the user.

3. The method of claim 1 further including a step:

controlling advertising material presented to the user with said one on or more recommendations based on which of said one or more policies is used to generate to said one or more recommendations.

4. The method of claim 1, wherein a different policy can be used for each request for a recommendation made by the user, so that said one or more policies are utilized on a request by request basis.

5. The method of claim 1, further including a step:

comparing a policy influenced recommendation to the user against a recommendation made by the recommender system in the absence of considering said one or more policies.

6. The method of claim 1, further including a step:

updating a policy record for a selected policy within a policy log when a recommendation is made to the user based on such selected policy.

7. The method of claim 6, further including a step:

generating a report of a number of recommendations made by a recommender system broken down according to a type of policy used for such recommendations.

8. The method of claim 1, wherein said policy is used to provide a preference to a policy holder, said preference being either a preference filter to be used against a list of recommendation items generated by the recommender system, and/or a presentation preference for one or more items associated with the policy holder and which are part of said list of recommendation items.

9. The method of claim 1, wherein said policy is defined with reference to a period of time in which the policy is to be used.

10. The method of claim 1, wherein said policy is defined with reference to one or more keywords associated with when the policy is to be used.

11. The method of claim 1, wherein said policy is defined with reference to one or more demographic variables associated with the user.

12. The method of claim 1, wherein said policy is defined with reference to a type characteristic associated with each of the items recommended by the recommender system.

13. The method of claim 1, wherein said policy is defined with reference to a release date associated with the items recommended by the recommender system.

14. The method of claim 1, wherein said policy is defined with reference to a brand or source of the items recommended by the recommender system.

15. The method of claim 1, wherein multiple policies are evaluated for each recommendation made by the recommender system.

16. The method of claim 1, wherein the recommender system is implemented at an e-commerce website.

17. The method of claim 1, wherein the recommender system is implemented at least in part in a client computing device, including a programming receiver.

18. The method of claim 1, wherein said one or more policies are considered after a recommender system has generated an initial list of uninfluenced recommendations.

19. The method of claim 1, wherein at least one of said one more policies is utilized by a recommender system while formulating an initial list of recommendations.

20. The method of claim 1, wherein the recommendation is associated with a book, a movie, an auction item, or a content item.

21. The method of claim 1, wherein at least a first one of the policies includes a fulfillment requirement, so that the recommender system is forced to generate a certain number of recommendations based on said first one of the policies.

22. The method of claim 1, wherein policies are selected on a controlled opportunity basis to influence recommendations, such that a first policy can have a higher percentage chance of influencing a recommendation compared to a second policy.

23. A method of presenting advertising in conjunction with recommendations made by a recommender system, the method comprising the steps of:

(a) implementing at least one predetermined policy to be used for influencing recommendations made by the recommender system to a user;

(b) responding to a request for a recommendation from a user;

(c) presenting advertising content to said user based on said at least one predetermined policy while presenting one or more policy influenced recommendations to the user in response to said request.

24. The method of claim 23, wherein the request is made by a user during an online Internet session.

25. The method of claim 23, wherein the request is made by a user from a home based content receiver.

26. The method of claim 23, wherein said advertising content is based on recommendation content presented in said one or more policy influence recommendations.

27. The method of claim 26, wherein an advertiser associated with said one or more policy influence recommendations is automatically selected as a source of said advertising for said advertising content.

28. The method of claim 23, wherein said advertising content is presented based on a pay for placement request from an advertiser.

29. The method of claim 27, wherein said one or more policy influenced recommendations are also presented based on a pay for policy request from an advertiser.

30. In a recommender system which operates at an Internet website and is programmed with to provide recommendations to users for items in response to a request for a recommendation, the improvement comprising:

(a) a first software routine for setting up one or more policies to be used for influencing recommendations made by the recommender system to a user;

wherein the recommender system is caused to use at least one of said one or more policies to present one or more policy influenced recommendations to the user in response to the request for a recommendation.